Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).     

Biomarkers on patient T cells diagnose active tuberculosis and monitor treatment response

BACKGROUND. The identification and treatment of individuals with tuberculosis (TB) is a global public health priority. Accurate diagnosis of pulmonary active TB (ATB) disease remains challenging and relies on extensive medical evaluation and detection of Mycobacterium tuberculosis (Mtb) in the patient’s sputum. Further, the response to treatment is monitored by sputum culture conversion, which takes several weeks for results. Here, we sought to identify blood-based host biomarkers associated with ATB and hypothesized that immune activation markers on Mtb-specific CD4⁺ T cells would be associated with Mtb load in vivo and could thus provide a gauge of Mtb infection.METHODS. Using polychromatic flow cytometry, we evaluated the expression of immune activation markers on Mtb-specific CD4⁺ T cells from individuals with asymptomatic latent Mtb infection (LTBI) and ATB as well as from ATB patients undergoing anti-TB treatment.RESULTS. Frequencies of Mtb-specific IFN-γ⁺CD4⁺ T cells that expressed immune activation markers CD38 and HLA-DR as well as intracellular proliferation marker Ki-67 were substantially higher in subjects with ATB compared with those with LTBI. These markers accurately classified ATB and LTBI status, with cutoff values of 18%, 60%, and 5% for CD38⁺IFN-γ⁺, HLA-DR⁺IFN-γ⁺, and Ki-67⁺IFN-γ⁺, respectively, with 100% specificity and greater than 96% sensitivity. These markers also distinguished individuals with untreated ATB from those who had successfully completed anti-TB treatment and correlated with decreasing mycobacterial loads during treatment.CONCLUSION. We have identified host blood-based biomarkers on Mtb-specific CD4⁺ T cells that discriminate between ATB and LTBI and provide a set of tools for monitoring treatment response and cure.TRIAL REGISTRATION. Registration is not required for observational studies.FUNDING. This study was funded by Emory University, the NIH, and the Yerkes National Primate Center.     

Epitope load identifies kidney transplant recipients at risk of allosensitization following minimization of immunosuppression

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Alcohol consumption patterns and predictors of use following liver transplantation for alcoholic liver disease.

For patients who receive a liver transplant (LTX) for alcoholic liver disease (ALD), investigators are focusing beyond survival to determine specific alcohol use outcomes. Studies suggest the use of alcohol ranges from 8 to 22% for the first post-transplant year with cumulative rates reaching 30 to 40% by 5 years following transplantation. Yet while investigators are interested in determining specific rates of alcohol use and predictors of use, only three studies since 1990 have been prospective. In 1998, we began a prospective study of post-LTX alcohol consumption in ALD recipients using multiple repeated measures of alcohol use. After 5 years of follow-up, we found that 22% had used any alcohol by the first year and 42% had a drink by 5 years. By 5 years, 26% drank at a heavier use (binge) pattern and 20% drank in a frequent pattern. In a univariate model, predictors of alcohol use included pre-transplant length of sobriety, a diagnosis of alcohol dependence, a history of other substance use, and prior alcohol rehabilitation.     

Predictive factors of stroke in patients undergoing coronary bypass grafting: statins are protective.

BACKGROUND: Despite major improvement in surgical techniques and intensive care management, stroke remains one of the most devastating complications of coronary artery bypass grafting (CABG). We aimed to determine factors predicting the occurrence of stroke during CABG. A special interest was focused on preoperative therapies. METHODS: We prospectively enrolled 810 consecutive candidates for CABG alone in a specific database, including all pre- and perioperative data (history, clinical, therapeutic, cardiac catheterization, surgical and intensive care data). Univariate tests and then multiple logistic regression analysis were used to determine independent predictive factors. RESULTS: During the first postoperative month, stroke occurred in 11 cases and transient ischemic attack (TIA) in 4 additive cases (cumulative rate: 1.85%). After the multivariate analysis, the following factors remained significant (p<0.05) in the predictive model, with corresponding odds ratios between brackets: redo cardiac surgery (7.45), unstable cardiac status (4.74), past history of cerebrovascular disease (4.14), past history of peripheral arterial disease (3.55), whereas the presence of preoperative statins was protective (0.24, 95% IC: 0.07-0.78). The addition of perioperative data (aortic calcification, postoperative arrhythmia, on/off-pump surgery) did not change the final predictive model. CONCLUSION: To our knowledge, this is the first real-world observational report highlighting the interest of statins for the prevention of stroke in the very special situation of CABG. Even though according to randomized trials coronary patients have a benefit from these drugs, a special level of interest should be directed towards those presenting the above-mentioned risk factors.     

Anxiety in medically III patients

Anxiety disorders and anxiety symptoms are highly prevalent in the general population and more so in the medically ill. They have a number of negative consequences for these patients and may worsen the outcome of the medical illness and increase health care utilization. In the evaluation of these patients, it is of paramount importance to identify the etiology of the anxiety and, in particular, to differentiate primary from secondary anxiety. Management includes medications (especially benzodiazepines and selective serotonin reuptake inhibitors) and psychotherapy (particularly cognitive-behavioral therapy).